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A Framework for Developing the Structure of Public Health Economic Models

Overview of attention for article published in Value in Health (Elsevier Science), July 2016
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

policy
1 policy source
twitter
4 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
29 Dimensions

Readers on

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153 Mendeley
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Title
A Framework for Developing the Structure of Public Health Economic Models
Published in
Value in Health (Elsevier Science), July 2016
DOI 10.1016/j.jval.2016.02.011
Pubmed ID
Authors

Hazel Squires, James Chilcott, Ronald Akehurst, Jennifer Burr, Michael P. Kelly

Abstract

A conceptual modeling framework is a methodology that assists modelers through the process of developing a model structure. Public health interventions tend to operate in dynamically complex systems. Modeling public health interventions requires broader considerations than clinical ones. Inappropriately simple models may lead to poor validity and credibility, resulting in suboptimal allocation of resources. This article presents the first conceptual modeling framework for public health economic evaluation. The framework presented here was informed by literature reviews of the key challenges in public health economic modeling and existing conceptual modeling frameworks; qualitative research to understand the experiences of modelers when developing public health economic models; and piloting a draft version of the framework. The conceptual modeling framework comprises four key principles of good practice and a proposed methodology. The key principles are that 1) a systems approach to modeling should be taken; 2) a documented understanding of the problem is imperative before and alongside developing and justifying the model structure; 3) strong communication with stakeholders and members of the team throughout model development is essential; and 4) a systematic consideration of the determinants of health is central to identifying the key impacts of public health interventions. The methodology consists of four phases: phase A, aligning the framework with the decision-making process; phase B, identifying relevant stakeholders; phase C, understanding the problem; and phase D, developing and justifying the model structure. Key areas for further research involve evaluation of the framework in diverse case studies and the development of methods for modeling individual and social behavior. This approach could improve the quality of Public Health economic models, supporting efficient allocation of scarce resources.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Portugal 1 <1%
Unknown 151 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 20%
Researcher 26 17%
Student > Master 24 16%
Other 13 8%
Student > Bachelor 9 6%
Other 28 18%
Unknown 23 15%
Readers by discipline Count As %
Medicine and Dentistry 31 20%
Economics, Econometrics and Finance 21 14%
Nursing and Health Professions 13 8%
Social Sciences 10 7%
Engineering 9 6%
Other 34 22%
Unknown 35 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 January 2020.
All research outputs
#4,469,108
of 17,361,274 outputs
Outputs from Value in Health (Elsevier Science)
#757
of 3,268 outputs
Outputs of similar age
#72,814
of 269,797 outputs
Outputs of similar age from Value in Health (Elsevier Science)
#16
of 111 outputs
Altmetric has tracked 17,361,274 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 3,268 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 269,797 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.